Ischemic stroke is the 4th leading cause of death in the U.S. and a major cause of disability. The etiology of stroke is multifactorial and poorly understood. Genetics is a potentially powerful tool for better understanding disease etiology as it can highlight biological mechanisms underlying disease and point the way to improved prevention and treatment. Efforts to decipher the genetic underpinnings of ischemic stroke have been hampered because of its heterogeneity. Our study addresses this problem by focusing on early-onset ischemic stroke (i.e., onset < 60 years), a particularly devastating manifestation of stroke because of its toll on child rearing and the ability to work. Early-onset ischemic stroke comprises ~ 20% of all first-ever stroke and this proportion is increasing. Studying early onset forms of other common genetic diseases (e.g., cancers, heart disease, diabetes) has provided valuable insights about disease etiology because of the enrichment of genetic causes. Our overall hypothesis is that early-onset ischemic stroke is enriched for genetic signals that may highlight biological mechanisms underlying stroke and point the way to improved prevention and treatment strategies. While the potential utility in studying early-onset ischemic stroke has been well recognized, a major limitation has been the accrual of large sample sizes. We have taken a large step to overcome the primary limitation of insufficient sample size by pulling together a multicenter early-onset stroke genetics consortium that includes up to 13,500 cases already genotyped for common and rare variants, the latter allowing us to test compelling hypotheses assessing the contribution of low frequency variants to early- onset stroke susceptibility. The primary goals of our study are to detect common and rare variants associated with early-onset ischemic stroke through genome-wide association analysis of GWAS and exome arrays in up to 13,500 early- onset ischemic stroke cases and 94,000 controls from 16 participating cohorts. For the newly discovered stroke-associated loci, we will identify causal variants, genes, and pathways using multiple bioinformatics approaches. We will also determine if the newly discovered stroke-associated loci are also associated with older onset stroke and with serum levels of biomarkers reflective of prothrombotic activity. Finally, we will test for shared genetic risk between early-onset IS and deep venous thrombosis using polygenic risk scores and LD regression. The successful identification of novel pathways and drug targets has the potential to transform our understanding of the stroke pathophysiology and lead to more effective preventive strategies. Our study will leverage the advantages of early-onset IS cases for genetic studies, and will also be the most well-powered examination to date of the role of rare variants in early onset IS etiology. The proposed study will establish a unique resource for continued studies of the genetic basis of IS, complementary to studies in older adults.